[GitHub] [hudi] vinothchandar commented on a change in pull request #3549: [HUDI-2369] Blog on bulk_insert sort modes

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vinothchandar commented on a change in pull request #3549:
URL: https://github.com/apache/hudi/pull/3549#discussion_r700624615



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File path: website/blog/2021-08-27-bulk-insert-sort-modes.md
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+---
+title: "Bulk Insert Sort Modes with Apache Hudi"
+excerpt: "Different sort modes available with BulkInsert"
+author: shivnarayan
+category: blog
+---
+
+Apache Hudi supports a `bulk_insert` operation in addition to "insert" and "upsert" to ingest data into a hudi table. 
+There are different sort modes that one could employ while using bulk_insert. This blog will talk about 
+different sort modes available out of the box, and how each compares with others. 
+<!--truncate-->
+
+Apache Hudi supports “bulk_insert” to assist in initial loading to data to a hudi table. This is expected
+to be faster when compared to using “insert” or “upsert” operations. Bulk insert differs from insert in two
+aspects. Existing records are never looked up with bulk_insert, and some writer side optimizations like 
+small files are not managed with bulk_insert. 
+
+Bulk insert offers 3 different sort modes to cater to different needs of users, based on the following principles.
+
+- Sorting will give us good compression and upsert performance, if data is laid out well. Especially if your record keys 
+  have some sort of ordering (timestamp, etc) characteristics, sorting will assist in trimming down a lot of files 
+  during upsert. If data is sorted by frequently queried columns, queries will leverage parquet predicate pushdown 
+  to trim down the data to ensure lower latency as well.
+  
+- Additionally, parquet writing is quite a memory intensive operation. When writing large volumes of data into a table 
+  that is also partitioned into 1000s of partitions, without sorting of any kind, the writer may have to keep 1000s of 
+  parquet writers open simultaneously incurring unsustainable memory pressure and eventually leading to crashes.
+  
+- It's also desirable to start with the smallest amount of files possible when bulk importing data, as to avoid 
+  metadata overhead later on for writers and queries. 
+
+3 Sort modes supported out of the box are: `PARTITION_SORT`,`GLOBAL_SORT` and `NONE`.
+
+## Configurations 
+One can set the config [“hoodie.bulkinsert.sort.mode”](https://hudi.apache.org/docs/configurations.html#withBulkInsertSortMode) to either 
+of the three values, namely NONE, GLOBAL_SORT and PARTITION_SORT. Default sort mode is `GLOBAL_SORT`.
+
+## Different Sort Modes
+
+### Global Sort
+
+As the name suggests, Hudi sorts the records globally across the input partitions, which maximizes the number of files 
+pruned using key ranges, during index lookups for subsequent upserts. This is because each file has non-overlapping 
+min, max values for keys, which really helps, when the key has some ordering characteristics such as a time based prefix.
+Given we are writing to a single parquet file on a single output partition path on storage at any given time, this mode
+greatly helps control memory pressure during large partitioned writes. Also due to global sorting, each small table 
+partition path will be written from atmost two spark partition and thus contain just 2 files. 
+This is the default sort mode with bulk_insert operation in Hudi. 
+
+### Partition sort
+In this sort mode, records within a given spark partition will be sorted. But there are chances that a given spark partition 
+can contain records from different table partitions. And so, even though we sort within each spark partitions, this sort
+mode could result in large number of files at the end of bulk_insert, since records for a given table partition could 
+be spread across many spark partitions. During actual write by the writers, we may not have much open files 
+simultaneously, since we close out the file before moving to next file (as records are sorted within a spark partition) 
+and hence may not have much memory pressure. 
+
+### None
+
+In this mode, no transformation such as sorting is done to the user records and delegated to the writers as is. So, 
+when writing large volumes of data into a table partitioned into 1000s of partitions, the writer may have to keep 1000s of
+parquet writers open simultaneously incurring unsustainable memory pressure and eventually leading to crashes. Also, 
+min max ranges for a given file could be very wide (unsorted records) and hence subsequent upserts may read 
+bloom filters from lot of files during index lookup. Since records are not sorted, and each writer could get records 
+across N number of table partitions, this sort mode could result in a huge number of files at the end of bulk import. 
+This could also impact your upsert or query performance due to large number of small files. 
+
+## User defined partitioner
+
+If none of the above built-in sort modes suffice, users can also choose to implement their own 
+[partitioner](https://github.com/apache/hudi/blob/master/hudi-client/hudi-client-common/src/main/java/org/apache/hudi/table/BulkInsertPartitioner.java)
+and plug it in with bulk insert as needed.
+
+## Bulk insert with different sort modes
+Here is a microbenchmark to show the performance difference between different sort modes.
+
+![Figure showing different sort modes in bulk_insert](/assets/images/blog/bulkinsert-sort-modes/sort-modes.png) <br/>

Review comment:
       its a bit misleading how sorting adds very little overhead for bulk_insert. thoughts?




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